Video noise reduction filters have been extensively used in both post-production and video compression environments. The former often require filters which preserve as much detail as possible, and therefore tend to use very conservative settings which may lead to uneven noise removal over the picture. The latter often require high filtering strength, even at the expense of some loss in detail, because the goal is to reduce the amount of information in the video and thereby increase compression efficiency (that is, reduce bit rate).
Video filtering can be performed in the pixel domain or in a transform domain such as Fourier or wavelet. Pixel-based video filtering methods typically reduce noise by averaging each pixel with a number of other pixels. In pixel-based spatial filtering, these other pixels are usually spatial neighbors. Known techniques of pixel-based spatial filtering include median filters. In temporal filtering, these other pixels are typically temporally predicted pixels from n nearby reference frames. Previous pixel-based video filtering methods have combined spatial and temporal filtering in various ways.